{
    "action": "tool_call",
    "reasoning": "I need to determine which numeric metric is most important. Looking at the evidence, this is a boxing matches dataset with Fighter A vs Fighter B records. The most fundamental metric in boxing is wins - it directly determines success. The evidence shows won_A and won_B columns with significant ranges (won_A: 0-332, won_B: 0-251) and high averages (23.1 and 15.2 respectively). I should query for the records with the highest and lowest win counts to show the extremes of this key metric. I'll look at both fighters' wins to be comprehensive.",
    "tool": "query_sql",
    "args": {
        "sql": "WITH ranked_matches AS (SELECT won_A, won_B, lost_A, lost_B, drawn_A, drawn_B, kos_A, kos_B, age_A, age_B, stance_A, stance_B, result, decision, won_A + won_B as total_wins FROM raw.boxing_matches) SELECT won_A, won_B, total_wins, lost_A, lost_B, kos_A, kos_B, age_A, age_B, stance_A, stance_B, result, decision FROM ranked_matches WHERE total_wins >= (SELECT MAX(won_A + won_B) FROM raw.boxing_matches) OR total_wins <= (SELECT MIN(won_A + won_B) FROM raw.boxing_matches) ORDER BY total_wins DESC LIMIT 50",
        "purpose": "Find records with highest and lowest total wins (won_A + won_B) to show extremes of the most important metric",
        "source": "raw"
    }
}